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单羧酸转运蛋白4 (MCT4)对接受PD-1抑制剂治疗的肺腺癌患者的预测价值
Authors Zhang Q , Pan G, Zhang L , Xu Y , Hao J
Received 29 August 2024
Accepted for publication 28 November 2024
Published 6 December 2024 Volume 2024:17 Pages 10515—10531
DOI https://doi.org/10.2147/JIR.S493632
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Tara Strutt
Qinghua Zhang,1,* Guizhen Pan,2,* Lu Zhang,1 Yidan Xu,1 Jiqing Hao1
1Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People’s Republic of China; 2Department of Radiation Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Jiqing Hao, Department of Oncology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, People’s Republic of China, Tel +86 13965029739, Email haojiqing@ahmu.edu.cn
Purpose: Monocarboxylate transporter 4 (MCT4) can influence the amount of lactate in the tumor microenvironment and further control cancer cell proliferation, migration, and angiogenesis. This study aimed to evaluate the predictive value of MCT4 for prognosis and immunotherapy efficacy in advanced lung adenocarcinoma (LUAD).
Patients and methods: First, bioinformatics analysis was used to assess the relevance of MCT4 for survival and immunotherapy outcomes in LUAD. Subsequently, we performed a retrospective study involving 126 patients with stage IIIb to IV LUAD treated with programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors. MCT4 expression in LUAD tissues was detected by immunohistochemistry (IHC), then the patients were divided into high and low expression groups. The differences in the medical records of the two groups were compared using the X2 test. Kaplan-Meier (K-M) method was used for survival analysis. Univariate and multivariate analysis were used to pinpoint independent predictors, and a nomogram was developed based on the significant factors for overall survival (OS) in the multivariate analysis. The predictive ability of the nomogram was evaluated through C-index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).
Results: Both bioinformatics analysis and clinical study revealed that low MCT4 expression was associated with better prognosis and immunotherapy efficacy. Multivariate analysis of clinical characteristics showed that age > 65 years, stage IV, high MCT4 expression, neutrophil-to-lymphocyte ratio (NLR)> 3, lactate dehydrogenase (LDH)> 250 (U/L) and carcinoembryonic antigen (CEA)> 5 (ng/mL) were significantly associated with poor prognosis on immunotherapy. These factors were subsequently incorporated into the nomogram model. The C-index value of the model stood at 0.735 (95% CI= 0.662 ~ 0.807), indicating robust predictive performance of the model. The DCA curve showed that the model had a notable clinical application value.
Conclusion: High expression of MCT4 is associated with poor prognosis and reduced efficacy of immunotherapy in patients with advanced LUAD.
Keywords: lung adenocarcinoma, monocarboxylate transporter 4, immunotherapy efficacy, prognosis, nomogram